RESUMEN
One of the challenging issues in the formation of atomic wires in break-junction experiments is the formation of stable monoatomic chains of reasonable length. To address this issue, in this study, we present a combination of unsupervised and supervised machine learning models trained on the experimentally measured conductance traces, with a goal to develop a microscopic understanding. Applying a machine learning model to two independent data sets from two different samples containing 72 000 and 90 000 conductance-displacement traces of single-atomic junctions, respectively, we first obtain the optimum conditions of bias and the stretching rate for the formation of chains of length > 4 Å. A deep learning method is subsequently applied for the classification of individual breaking traces, leading to the identification of trace features related to long-chain formation. Further investigation by ab initio molecular dynamics simulations provides a molecular-level understanding of the problem.
RESUMEN
The three well-known orderings of the two constituting atomic species in a bimetallic nano-alloy - core-shell, Janus and mixed structural patterns - may be interconvertible depending on the synthesis conditions. Using first principles electronic structure calculations in the present work, we look for the microscopic origin for such structural transformation considering eight Pd-related bimetallic nano-alloys. Our analysis shows that it is the change in atom-atom covalency that is responsible for such structural transformation. Our study also reveals that the three patterns are distinctly identified in terms of total orbital hybridization. Finally, we have analyzed the trend in the relative catalytic activity for the three structures of each bimetallic nano-alloy using the d-band model. Our analysis indicates that the trend in the catalytic activity for the bimetallic Pd-X nano-alloys seems to be intermediate to those of the pristine Pd and Pt nano-clusters possessing similar structure and equal number of total atoms. Among the studied binary nano-alloys, the bimetallic Pd-Ni nano-alloy appears as the most suitable binary pair to develop a non-Pt catalyst.